With the ever increasing demand for bandwidth and end-to-end performance guarantees presented by emerging networked applications, high speed networking techniques have been evolving at rapid pace in recent years. One of the most promising enabling technologies is the cell switching and networking techniques of ATM which provides the core transport needed to support multiple services at extremely high speed and fast decreasing cost. Central to this new technology are ATM-based switches that are capable of supporting diverse end-to-end quality-of-services through effective resources and traffic management methods which allow for efficient sharing of switch and network resources.
In recognizing such needs, a number of standards organizations have specified the service classes and various traffic management interfaces and attributes for ATM networks and services. For example, ATM Forum has defined five service categories: constant bit rate ("CBR"), real time variable bit rate ("rt-VBR"), non-real time variable bit rate ("nrt-VBR"), available bit rate ("ABR") and unspecified bit rate ("UBR"). Quality of service (QoS) is parameterized for each service and can be requested at call setup time for switched and permanent virtual connections. From the perspective of an ATM switch, this presents a challenge to resource and traffic management since one must allocate and share, in real-time, the resources efficiently among diverse services requested by connections.
As an example, a generic output-queuing ATM switch on a single ATM interface card 10 shown in FIG. 1. Typically such a card includes multiple physical ports 20 such as e.g., T1, DS3 and OC-3 ports. At each physical port, there are typically multiple queues 30 associated with multiple service classes such as CBR, rt-VBR, etc. In the extreme case there may be per-VC queuing. A buffer 40 is provided that may be shared by all the queues at all the ports or at least among queues for a single port. The bandwidth is shared through e.g., some variation of a weighted round-robin discipline as indicated by link schedulers 15 in FIG. 1.
In a queuing-theoretic framework, the ATM switch of FIG. 1 translates to a multi-queue, multi-server environment with a round-robin service discipline within the service classes at a port and a shared buffer across all the ports. From the QoS point of view, the focus relates to the performance bounds for individual connections or at least on a per-queue (class) basis. The literature is severely limited in terms of results for such queuing systems even in the case of a single-server system, however, there has been recent work done on deterministic performance bounds for generalized processor sharing queuing systems, e.g., as described in A. K. Parekh and R. Gallager, "A Generalized Processor Sharing Approach to Flow Control in Integrated Services Networks: The Single Node Case," IEEE/ACM Transactions on Networking, Vol. 1, No. 3, pp. 344-357, June 1993, hereby incorporated by reference as if fully set forth herein. However, these deterministic bounds are typically fairly loose, lead to poor link utilization and hence are of limited usefulness.
There has also been work on statistical performance bounds which appear promising, but more work needs to be done to make these bounds suitable for a real-time call admission control ("CAC"). See, Zhi-li Zhang, et al., "Statistical Analysis of Generalized Processor Sharing Scheduling Discipline," IEEE Journal of Selected Areas in Communication Vol. 13, No. 6 p 1071-80 (August 1995), hereby incorporated by reference as if fully set forth herein.
There however, exists literature on performance bounds for single-queue, single-server fluid models. Additionally, the related problem of Call Admission Control in these systems has been studied extensively where the typical problem addressed is how to estimate the steady state loss or delay performance given fixed buffer and bandwidth resources and a set of connections with specified traffic descriptors and given QoS requirements. In reality, however, buffer and bandwidth are, and need to be, shared among several services as connections arrive and depart in unpredictable patterns. Thus, it would be highly desirable to provide a dynamic scheme by which bandwidth and buffer are managed simultaneously and dynamically allocated to each service. See also Keith Ross, "Multiservice Loss Models in Broadband Telecommunication Networks" (1995) and Raffaele Bolla et al., "Bandwidth Allocation and Admission Control in ATM Networks with Service Separation," IEEE Communications Magazine Vol. 35, No. 5 (May 1997), hereby incorporated by reference as if fully set forth herein. These references consider dynamic bandwidth allocation but do not consider the buffer resource. Additionally, "Bandwidth Allocation and Admission Control in ATM Networkds with Service Separation," supra, only allows for homogenous connections, i.e., identical traffic parameters, and QoS requirements within a service class. This is not a realistic scenario in practice.